Ramos, "Multi-kernel gaussian processes," in Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two, ser. IJCAI'11. AAAI Press, 2011, pp. 1408-1413.A. Melkumyan and F. Ramos, "Multi-kernel Gaussian Processes," in International Joint ...
he had the opportunity to explore a wide variety of predominantly Bayesian methods for the purpose of modelling human motion. More specifically, he worked extensively, among others, on Bayesian nonparametrics, Gaussian processes, variational Bayes and MCMC sampling (Gibbs,...
To mitigate the negative effects noise, we improved the channel shuffle algorithm by adding the image processing technique (Gaussian filtering). 3.4. Computation reduction To reduce the deep learning network's computational burden without performance decline, some approaches have been carried out in ...
In the context of our deep learning methods, we employed a Random Search 5-folds cross-validation for the hyperparameters tuning. Also, in this case, all the experiments were carried out using a Gaussian radial basis kernel for the Kernel PCA step. For all the DeepMKL models, we fixed the...
[19] used the ELM model and Gaussian Process Regression (GPR) to predict water level. They used the historical datasets at four previous time steps to predict water levels. The ELM was able to successfully water level. Seidu et al. [20] coupled wavelet transform-self adaptive differential ...
Finally,Pvalues are attributed toi_kassuming that theu_{i_k}^{{\varvec{\ell }}}values obey a multivariate Gaussian distribution (null hypothesis) as \begin{aligned} P_{i_k} = P_{\chi ^2} \left[ > \sum _{{\varvec{\ell }}}\left( \frac{u_{i_k}^{{\varvec{\ell }}}{\...
Gaussian processesRegressionAtrophyBSIMulti-kernel learningMRIPET Alzheimer’s diseaseMild cognitive impairmentMachine learning approaches have had some success in predicting conversion to Alzheimer's Disease (AD) in subjects with mild cognitive impairment (MCI), a less serious condition that nonetheless is...
The kernel function employed in this algorithm utilizes a Gaussian kernel, and the elements within the kernel matrix can be computed using the following formula, 𝑘𝑚(𝐱𝑖,𝐱𝑗)=exp(−1𝜎2𝑘(‖𝐱𝑖−𝐱𝑗‖2)).kmxi,xj=exp−1σk2xi−xj2. (25) The exponent ...
GAUSSIAN processesREGRESSION analysisFIXED effects modelTYPE 2 diabetesISING modelAnalyzing correlated high‐dimensional data is a challenging problem in genomics, proteomics, and other related areas. For example, it is important to identify significant genetic pathway effects associated with biomarkers...
Rashid.A Bayesian model averaging based multi-kernel Gaussian process regression framework for nonlinear state estimation and quality prediction of multiphase batch processes with transient dynamics and uncertainty[J]. Chemical Engineering Science .2013...